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The performance of the proposed approach is compared for classification accuracy with another efficient method based on global linear regression on hybrid eigenface (HGLR). They also investigate the effect of number of images used to construct hybrid-eigenfaces on classification accuracy. Experimental results on two well known publicly available face databases demonstrate the effectiveness of the proposed approach. The suitability of proposed approach is also noticed when the number of available images is small.<\/p>","DOI":"10.4018\/ijcvip.2012040104","type":"journal-article","created":{"date-parts":[[2012,10,22]],"date-time":"2012-10-22T12:06:06Z","timestamp":1350907566000},"page":"48-58","source":"Crossref","is-referenced-by-count":4,"title":["Local Linear Regression on Hybrid Eigenfaces for Pose Invariant Face Recognition"],"prefix":"10.4018","volume":"2","author":[{"given":"Ajay","family":"Jaiswal","sequence":"first","affiliation":[{"name":"Jawaharlal Nehru University, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nitin","family":"Kumar","sequence":"additional","affiliation":[{"name":"Jawaharlal Nehru University, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R. 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